Learning temporal relationships between symbols with laplace neural manifolds
Firing across populations of neurons in many regions of the mammalian brain maintains a
temporal memory, a neural timeline of the recent past. Behavioral results demonstrate that …
temporal memory, a neural timeline of the recent past. Behavioral results demonstrate that …
[HTML][HTML] Efficient coding in biophysically realistic excitatory-inhibitory spiking networks
The principle of efficient coding posits that sensory cortical networks are designed to encode
maximal sensory information with minimal metabolic cost. Despite the major influence of …
maximal sensory information with minimal metabolic cost. Despite the major influence of …
Continuous Attractor Networks for Laplace Neural Manifolds
BC Daniels, MW Howard - Computational Brain & Behavior, 2025 - Springer
Many cognitive models, including those for predicting the time of future events, can be
mapped onto a particular form of neural representation in which activity across a population …
mapped onto a particular form of neural representation in which activity across a population …
A meta reinforcement learning account of behavioral adaptation to volatility in recurrent neural networks
Natural environments often exhibit various degrees of volatility, ranging from slowly
changing to rapidly changing contingencies. How learners adapt to changing environments …
changing to rapidly changing contingencies. How learners adapt to changing environments …
Delineating the unique functional contribution of the retrosplenial cortex in the hippocampal-diencephalic-cingulate network
S Yanakieva - 2023 - orca.cardiff.ac.uk
The research described in this thesis investigates the unique anatomy of the retrosplenial
cortex and its functional contributions to spatial working memory in the rat. The retrosplenial …
cortex and its functional contributions to spatial working memory in the rat. The retrosplenial …